Analyst firm McKinsey & Company has published a new report on the potential impact of artificial intelligence (A.I.) on the job market, and it’s well worth a read. For employers on the hunt for tech pros skilled in A.I. and machine learning, it also offers some sobering statistics about the number of experts currently available. (For those experts, however, the news about stratospheric demand for A.I. talent is good—maybe it’s time to ask about that Tesla during your next round of salary-and-perk negotiations.)

The firm defines “artificial intelligence” in its report as “shorthand for deep learning techniques that use artificial neural networks.” Its analysts explored three different neural network techniques: “feed forward” neural networks, in which information moves through the network’s architecture without looping or refinement; “recurrent” neural networks, in which inputs are “looped” in order to boost performance; and “convolutional” neural networks, which are modeled after the complexity of the “animal visual cortex.”

Related to that, the firm, analyzed the utility of generative adversarial networks (GANs) and reinforcement learning, both of which are used to improve the performance of neural networks.

“We collated and analyzed more than 400 use cases across 19 industries and nine business functions,” the report explained. “They provided insight into the areas within specific sectors where deep neural networks can potentially create the most value, the incremental lift that these neural networks can generate compared with traditional analytics… and the voracious data requirements—in terms of volume, variety, and velocity—that must be met for this potential to be realized.”

In theory, A.I. will become very useful in detecting anomalies in workflows (industrial companies, for example, have been very big on using this capability to improve maintenance of engines and other hardware), optimizing real-time forecasts, and even customer service (think of Amazon’s product recommendations on steroids).

“We estimate that the A.I. techniques we cite in this briefing together have the potential to create between $3.5 trillion and $5.8 trillion in value annually across nine business functions in 19 industries,” the report stated. “This constitutes about 40 percent of the overall $9.5 trillion to $15.4 trillion annual impact that could potentially be enabled by all analytical techniques.”

Sounds pretty good, right? Especially since the firm estimates that fewer than 10,000 people actually have the skill to wrestle with the world’s biggest A.I. problems—for those tech pros, money and perks are already excellent, as other sources have repeatedly suggested, and may only get better. Companies will face a lot of issues in locking down the talent they need, especially if they don’t have the budget of an Apple or Google, but the A.I.-derived revenues may well prove worth these talent challenges.

However, given the complexity of A.I. and machine learning, none of this will happen overnight. It’s easy to forget that technological advances sometimes need decades to seize a firm toehold, especially in the face of what McKinsey terms “societal concerns and regulations.” So if you haven’t started educating yourself in A.I. yet, don’t worry—the market isn’t going to mature anytime soon. As for companies: recognize that A.I. will be big, but don’t expect an instant revolution.